Multispecies

SUPPLEMENTARY DATA

1 Introduction

NB: Graphs can be observed in full screen by a right click + “Open image in new tab”

2 Materials and Methods

All data processing was conducted in R version 4.4.0 (2024-04-24 ucrt) and Matlab 2021a. Significance levels are p < .0001 with “****”, p < .001 with “***”, p < .01 with “**”, p < .05 with “*”.

2.1 Biological models

SuppFig 2.A: Fauna models used in their sediment.

SuppFig 2.B: Fauna models used in their sediment.

Metabolic rate calculation

A model for Mass Specific Respiration rate (MSR) of aquatic invertebrates was developed by Brey (Brey 2010), providing a spreadsheet tool that implement an Artificial Neural Network (ANN). It requires as arguments : (1) individual body mass in J, (2) temperature, (3) depth in water, (4) taxonomic definition, (5) mobility mode (sessile, crawler, facultative or permanent swimmer/floater), (6) alimentation mode (carnivorous versus other modes), (7) vision type (yes or no defined as possession of image-forming eyes sensu (Seibel and Drazen 2007), i.e. an optical sense better than just light/dark separation), and (8) the starved state of the animal (yes or no). MSR calculation was made using the average energy density 21.4469 J.mgAFDW^{-1} (Brey et al. 2010), a depth of 1 m for intertidal species, and by default not starved. A conversion was done for the MSR from [J/J/day] to [mW.ind^{-1}]. Based on the theoretical frame of Brown and Allen ((Allen, Gillooly, and Brown 2005, @brown2004)), the individual metabolic rate I was expressed as function of the individual body size and the temperature. The equation was simplified to adjust the parameters r0, b and Ek for each species to the MSR results based on Brey ANN (Equation 2.A, Table 2.A).

I = r0.(IndivBodySize)^b . e^{\frac{-Ek}{(T+273,15)}} \tag{2.A}

Itot = I . Density \tag{2.B}

With the exponential part the factor Ek [K] is the ratio of E, activation energy over k Boltzmann’s constant (8.62×10−5 eV.K−1); r0 is the scaling constant; b is the scaling exponent; T is temperature [°C], IndivBodySize is the individual body size in Ash Free Dry Weigth [gAFDW.ind^{-1}], to get I [mW.ind{-1}]. Density is the spatial density of individuals in flume (based on sample surface) [ind.m^{-2}], thus Itot [mW.m^{-2}].

SuppTab 2.A: Species Brey Specific Metabolic Rate inputs and equation parameters results for Equation 2.A.

Species_Name	AphiaId	TaxaBrey	Mobility	Trophic	Vision	b	r0	Ek
Hediste diversicolor	152302	Annelida	Crawl	Deposit feeder	0	0.7733019	3.386977e+09	6197.232
Scrobicularia plana	141424	Mollusca 1	Sessile	Mixt Filter feeder	0	0.7752776	5.559549e+13	8986.158

Bioturbation processes

As far as the consequences on sediment erodibility are concerned, the influence of bioturbation should rather be divided into two main categories Figure 2.C: 1) whether the effect is chronic and generates a biogenic layer under standard hydrodynamic conditions (Mariotti and Fagherazzi 2012) or 2) whether it has an impact on the constituent layers of the sediment and is expressed in the case of high hydrodynamic events (mass erosion, roughly above 1Pa bed shear stress). Second, these effects can be characterized according to the type of consequence: either stabilizing by reinforcing physical protection and cohesion between particles or destabilizing by increasing surface roughness or modifying the rheology of sediments facilitating erosion when tidal currents or wave-induced turbulence are present Willows, Widdows, and Wood (1998). Several processes are possible in each case, for chronic effects, two kinds of processes were identified:

1. Passive processes relative to hydrodynamics modifications: 1a) Allogenic skimming flow operates when a high density of biogenic structures creates locally reduced hydrodynamic conditions, favouring the deposition of fine particles and the consolidation of sediments; 1b) Autogenic roughness causes a modification of hydrodynamic conditions on a very local scale by increasing the bed shear stress and the flow regime.

2. Active processes: 2a) Biodeposition is carried out by suspension feeders, which capture fine particles in suspension and agglomerate them into pseudo-faeces or faeces, leading to a muddification of the sedimentary bed. When combined with the biodiffusion effect, it increases particle mixing and sediment stability, while also promoting the development of MPB biofilms; 2b) Bioresuspension occurs when individuals produce tracks in relation to displacement or feeding behaviours (producing faecal pellets and/or pseudo- faeces) on the sediment surface, therefore generating a biogenic fluff layer. The amount of sediment reworked by this process may be limited by a high density or by a sufficient duration that will lead the bioturbating fauna to rework sediments that have already been reworked.

For the event-driven cases, two main processes were identified: 1) Biostabilization is a stabilisation against mass erosion by sedentary species which, by settling in galleries or tubes, compact the sediment and bind the particles together with their mucus; 2) Bed destabilization causes anticipated mass erosion of the sediment assimilated to a massive loss of the surficial part of sediment at a centimetre scale, and occurs when endogenous species are mobile in the sediment (biodiffusors or regenerators).

Types of bioturbation processes

SuppFig 2.C: The different types of bioturbation processes according to Kristensen et al. (2012) plus processes linked to sediment erodibility. Processes with green stars are stabilizing, with red stars are destabilizing.

Species classification references

SuppTab 2.B: Bibliographical references for the classification of the effects of bioturbation on sediment erodibility for the six model species.

	Chronic			Even-driven
	Stabilizing	Neutral	Destabilizing	Stabilizing	Neutral	Destabilizing
S. plana			(Soares and Sobral 2009) (Francis Orvain et al. 2005), (F. Orvain et al. 2007) (Kristensen et al. 2013) (Cozzoli et al. 2019)			(Francis Orvain et al. 2005), (F. Orvain et al. 2007)
H. diversicolor (Andersen and Pejrup 2011)		(Kristensen et al. 2013)	(Francis Orvain et al. 2018)	(Francis Orvain et al. 2018) (Passarelli et al. 2012) (Fernandes, Sobral, and Costa 2006) (Cozzoli et al. 2019)		(De Backer et al. 2010) (Cozzoli et al. 2019) (Smit et al. 2021)

2.2 Sediment and animal collection

The Schelde estuary, a macrotidal coastal estuary, situated between The Netherlands and Belgium, is split in two main parts, named Westerschelde (south part) and Oosterschelde (north part). Due to anthropological transformations, the Oosterschelde is no longer fed by Schelde freshwater (Figure 2.D).

SuppFig 2.D: Maps of sampling location for each species and sediment.

A muddy and a sandy sediment were collected in the Westerschelde (respectively mud in Groot Buitenschoor; sand in Rilland), wet-sieved at 5mm and stored 48h in a freezer, then wet-sieved at 1mm, to remove fauna and larger debris. Each sediment granulometry was characterized with a Mastersizer 2000 (Malvern Instruments Ltd., Malvern, UK). A 50%-50% vol mix was made, an let settle for a couple of weeks to reduce the water content. The water content, density, granulometry and organic matter were monitored all along the experiment. The granulometry of the stockpile is analysed once a week. The organic matter (OM) was obtained by loss on ignition: samples were placed in an oven for 72 h to remove the water and then placed in an oven at 550°C for 6 h to burn the OM (results).

Granulometry graph

SuppFig 2.E: Main sizes particules sediment granulometry: in brown stars, mud and sand prior mixing, in grey circles sediment from fauna sampling sites, in colored circles, experimental sediment with its evolution during experiment.

Granulometry table

SuppTab 2.C: Granulometry table

	Field					Source		Stock
Parameter	2022-07-04	2022-07-15				2022-07-26		2022-06-03	2022-06-13	2022-06-17	2022-06-24	2022-07-01	2022-07-08	2022-07-13	2022-07-25	2022-07-29
	MACBA-SCRPL	CERED	CORVO	HEDDI	PERUL	Mud	Sand	Stock1	Stock2	Stock3	Stock4	Stock5	Stock6	Stock7	Stock8	Stock9
10% limit (10% < ...μm)	3.88	175.63	5.91	6.67	3.73	3.23	95.67	6.96	4.94	4.82	5.16	5.54	5.21	5.75	6.32	6.44
Median grainsize D50 in μm	28.00	287.05	51.51	52.99	25.33	20.69	158.83	82.25	53.14	45.99	68.97	62.91	58.58	70.82	81.31	87.92
Median grainsize D50 in PHI	5.16	1.80	4.28	4.24	5.30	5.60	2.65	3.60	NA	NA	3.86	3.99	4.09	3.82	3.62	3.51
Modus grainsize in μm	101.38	288.64	71.38	81.78	24.38	26.22	161.69	161.56	152.04	153.24	154.37	155.68	155.49	161.60	160.72	159.17
90% limit (90% < ...μm)	137.28	465.87	119.97	131.43	121.21	77.69	252.42	235.56	203.85	204.16	221.03	222.61	220.46	232.34	233.28	233.25
Coarse sand fraction PHI 0-1, 500-1000 μm	0.00	6.74	0.11	0.21	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Medium sand fraction PHI 1-2, 250-500 μm	0.66	56.89	0.53	0.32	0.81	0.83	10.53	8.07	4.02	4.19	6.28	6.61	6.32	7.72	7.77	7.71
Fine sand fraction PHI 2-3, 125-250 μm	11.90	35.70	8.08	11.17	8.56	3.13	62.81	29.04	26.71	25.77	27.48	26.10	26.18	27.73	29.05	30.27
Very Fine sand fraction PHI 3-4, 62.5-125 μm	19.75	0.68	31.89	31.52	16.10	10.44	23.15	17.54	17.23	16.33	17.53	17.39	16.74	16.18	17.49	18.01
Silt fraction <63 μm	67.89	0.00	59.80	57.13	74.73	85.79	3.53	45.46	52.04	53.71	48.80	50.02	50.87	48.48	45.80	44.11

Water content

SuppFig 2.F: Water content rate evolution during experiment and each temperature condition regression.

SuppFig 2.G: Water content rate versus temperature condition. The T high condition had significantly lower water content than the two other conditions.

Species were collected either in Oosterschelde or Westerschelde; C. edule in Oesterdam at first sampling then in Den Inkel; H. diversicolor in Haven Rattekaai; C. volutator in Haventje Ellewoutsdijk; S. plana and M. balthica in Den Inkel; P. ulvae in Nolleweg. Individuals of each species were sorted to create batches of size classes, and a sub-sample of each class were used to measure length, fresh weight, dry weight, Ash Free Dry Weight and define conversion coefficients that were used to create sample populations. The rest of the individuals were placed in the climatized mesocosm, an acclimation period of 2 weeks was respected before experiments.

Hediste diversicolor

Biometry done on each species and relation between all dimensions. Length: Length of shell [mm]; FW_shell: fresh weight with shell [g], FW: fresh weight of flesh [g], DW: Dry weight of flesh [g] (48h at 60°C), AFDW: ash free dry weight [g] (5h at 550°C).

Scrobicularia plana

Biometry done on each species and relation between all dimensions. Length: Length of shell [mm]; FW_shell: fresh weight with shell [g], FW: fresh weight of flesh [g], DW: Dry weight of flesh [g] (48h at 60°C), AFDW: ash free dry weight [g] (5h at 550°C).

2.3 Experimental design

Design

SuppFig 2.H: Experimental factors combinations.

Mesocosm tidal rythm

SuppFig 2.I: Mesocosms tidal rhythm for each duo. The blue arrow represents the respiration measure and the installation in the pot, the red arrow the bioturbation phase.

Sample composition

SuppFig 2.J: Sample biological levels in number of individuals on cores

2.4 Experimental measurement

Summary of data collected

SuppTab 2.D: Data set summary

Characteristic	Control			Small S. plana & H. diversicolor			Medium S. plana & H. diversicolor			Big S. plana & H. diversicolor
	T. medium, N = 61	T. low, N = 31	T. high, N = 31	T. medium, N = 81	T. low, N = 81	T. high, N = 81	T. medium, N = 81	T. low, N = 81	T. high, N = 91	T. medium, N = 81	T. low, N = 81	T. high, N = 91
Experimental design
Ambiant temperature (°C)	17.85+/-0.00	17.50+/-0.00	24.65+/-0.00	18.38+/-2.79	16.55+/-0.41	20.38+/-3.99	18.38+/-2.79	16.55+/-0.41	20.57+/-3.78	18.38+/-2.79	16.55+/-0.41	20.57+/-3.78
Mesocosm temperature (°C)	13.28+/-0.01	9.32+/-0.00	18.20+/-0.00	13.28+/-0.23	9.33+/-0.62	18.20+/-1.15	13.28+/-0.23	9.32+/-0.62	18.19+/-1.07	13.26+/-0.22	9.32+/-0.62	18.19+/-1.07
Metabolic rate in mesocosm (mW/m²)	0.00-0.00	0.00-0.00	0.00-0.00	9.57-19.72	5.88-10.50	15.31-32.25	17.48-29.99	12.05-19.47	22.03-58.14	25.61-46.29	18.43-31.05	42.82-81.93
Species 1 Metabolic rate in mesocosm (mW/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-19.72	0.00-10.50	0.00-32.25	0.00-29.99	0.00-16.58	0.00-58.14	0.00-46.29	0.00-25.82	0.00-81.93
Species 2 Metabolic rate in mesocosm (mW/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-13.84	0.00-8.85	0.00-24.41	0.00-20.44	0.00-19.47	0.00-43.50	0.00-35.33	0.00-31.05	0.00-64.03
Species 1 density in sample (ind/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00	0.00-160.00
Species 2 density in sample (ind/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00	0.00-320.00
Species 1 biomass in sample (gAFDW/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-7.56	0.00-6.17	0.00-5.84	0.00-12.99	0.00-11.13	0.00-12.48	0.00-22.87	0.00-19.94	0.00-19.53
Species 2 biomass in sample (gAFDW/m²)	0.00-0.00	0.00-0.00	0.00-0.00	0.00-3.61	0.00-3.17	0.00-4.09	0.00-5.98	0.00-8.71	0.00-8.63	0.00-12.66	0.00-15.93	0.00-14.23
Metabolic rate based on respiration meas (mW/m²)	0.00+/-0.00	0.00+/-0.00	0.00+/-0.00	13.20+/-8.76	12.25+/-9.76	23.74+/-9.75	30.61+/-5.64	17.38+/-6.28	41.85+/-15.14	34.59+/-25.24	41.76+/-12.44	65.71+/-25.64
Results
Bed Shear Stress (Pa)	7.31+/-0.51	3.32+/-1.26	3.13+/-0.49	4.43+/-2.50	2.49+/-1.36	4.52+/-1.20	2.51+/-1.32	2.69+/-1.57	3.81+/-1.26	2.55+/-1.26	3.06+/-1.65	3.28+/-1.32
1 Mean+/-SD; Minimum-Maximum

MSR levels of respiration samples

SuppFig 2.K: Sample composition for each duo in metabolic rates (MSR calculated with mesocosm T°).

3 Results

3.1 Respiration measurements

Respirometry results

SuppFig 3.A: All respirometry results for OsCar runs

SuppFig 3.B: All respirometry results for OsCar runs

Respirometry table

SuppTab 3.A: Respiration data summary

Characteristic	Small S. plana & H. diversicolor			Medium S. plana & H. diversicolor			Big S. plana & H. diversicolor
	T. low, N = 8	T. medium, N = 10	T. high, N = 9	T. low, N = 9	T. medium, N = 10	T. high, N = 10	T. low, N = 9	T. medium, N = 10	T. high, N = 10
Temperature mesocosm (°C)
Mean (SD)	9.33 (0.62)	13.28 (0.20)	18.20 (1.07)	9.32 (0.58)	13.28 (0.20)	18.19 (1.01)	9.32 (0.58)	13.26 (0.19)	18.19 (1.01)
Range	8.87, 10.83	13.07, 13.70	17.23, 20.08	8.87, 10.83	13.07, 13.70	17.23, 20.08	8.87, 10.83	13.07, 13.70	17.23, 20.08
Respiration Rate (µmolO2/s-1)
Mean (SD)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 (0.00)
Range	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.00	0.00, 0.01
Itot based on respiration meas (mW/m²)
Mean (SD)	12.25 (9.76)	10.56 (9.52)	21.10 (12.07)	15.45 (8.25)	24.49 (13.83)	37.67 (19.47)	37.12 (18.14)	27.67 (26.61)	59.13 (31.88)
Range	0.00, 29.59	0.00, 26.95	0.00, 37.36	0.00, 24.60	0.00, 36.40	0.00, 67.75	0.00, 61.20	0.00, 85.51	0.00, 97.42
Respiration Rate (µmolO2/gAFDW-1)
Mean (SD)	0.21 (0.14)	0.19 (0.15)	0.29 (0.11)	0.12 (0.06)	0.21 (0.05)	0.27 (0.11)	0.16 (0.07)	0.15 (0.14)	0.24 (0.10)
Range	0.05, 0.50	0.02, 0.47	0.14, 0.48	0.02, 0.20	0.14, 0.29	0.07, 0.44	0.08, 0.28	0.00, 0.43	0.08, 0.38
Unknown	1	2	1	1	2	1	1	2	1

ANCOVA results

SuppFig 3.C: ANCOVA results

SuppTab 3.B: ANCOVA results

Respiration_rate_mWm2..y_tf ~ Itot_meso_mWm2_Respi..x_tf + Mumo_txt + Cond_Fact_txt
Characteristic	Beta1	SE2	p-value
(Intercept)	0.8877***	1.535 × 10−4	2.350 × 10−187
Itot at mesocosm temperature - transf (mW/m²)	0.0001***	1.331 × 10−5	8.377 × 10−13
Mumo_txt	NA***		9.506 × 10−5
S. plana	-0.0004***	8.219 × 10−5	1.600 × 10−5
S. plana & (H. diversicolor)	0.0000	8.011 × 10−5	0.833
(S. plana) & H. diversicolor	0.0002**	7.982 × 10−5	0.004
H. diversicolor	0.0001	8.000 × 10−5	0.163
Cond_Fact_txt	NA		0.208
T. low	0.0001	7.666 × 10−5	0.078
T. medium	0.0000	6.556 × 10−5	0.515
T. high	-0.0001	8.096 × 10−5	0.37
No. Obs. = 72; R² = 0.646; AIC = -920
Anova, F(2,65) = 1.61, p = 0.21, eta2[g] = 0.047
Respiration_rate_mWm2..y_tf ~ Itot_meso_mWm2_Respi..x_tf + Mumo_txt + Cond_Fact_txt post-hoc tests
Residuals are normal - Shapiro-Wilk: stat = 0.977, p-value = 0.213 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 0.987, p-value = 0.468 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.448, p-value = 0.246 (α=0.1)
There are 0 outliers in **
1 *p<0.05; **p<0.01; ***p<0.001
2 SE = Standard Error

Conditions of application

SuppTab 3.C: Data set description and application conditions

Variable	Control, N = 01	S. plana, N = 191	S. plana & (H. diversicolor), N = 181	(S. plana) & H. diversicolor, N = 181	H. diversicolor, N = 171	Overall, N = 721
Respiration_rate_mWm2 (dependent)	NA (NA)	29 (22)	28 (12)	36 (22)	39 (28)	33 (22)
Itot at mesocosm temperature (mW/m²)	NA (NA)	34 (21)	23 (11)	22 (12)	26 (16)	26 (16)
Temperature level
T. low	0	6	5	6	6	23
T. medium	0	6	6	6	5	23
T. high	0	7	7	6	6	26
Respiration_rate_mWm2 normality test
Data are not normal - Shapiro-Wilk: stat=0.900, p-value=3.06e-05 (α=0.1).
Data transformation - Box-Cox λ = 0.340; λ2 = 1
Transformed data are normal - Shapiro-Wilk: stat = 0.984, p-value = 0.505 (α=0.1)
Itot_meso_mWm2_Respi normality test
Data are not normal - Shapiro-Wilk: stat=0.943, p-value=0.00279 (α=0.1).
Data transformation - Box-Cox λ = 0.010; λ2 = 1
Transformed data are normal - Shapiro-Wilk: stat = 0.991, p-value = 0.875 (α=0.1)
Treatments subgroup check
Variances are homogeneic - Levene: F value = 0.609, p-value = 0.814 - (α=0.1)
Independence of covariate: Mumo_txt; Cond_Fact_txt have a significant relation with covariate
Regression slopes homogeneity is verified
Respiration_rate_mWm2..y_tf ~ Itot_meso_mWm2_Respi..x_tf + Mumo_txt + Cond_Fact_txt post-hoc tests
Residuals are normal - Shapiro-Wilk: stat = 0.977, p-value = 0.213 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 0.987, p-value = 0.468 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.448, p-value = 0.252 (α=0.1)
There are 0 outliers in **
1 Mean (SD); n

3.2 Erodibility analysis

3.2.1 Erosion data treatment

Global results

3.2.2 Erosion measurement treatment

SuppFig 3.D: Sketch of erosion processes in the fluff layer erosion (green line), mass erosion (solid red line) and the parameters used. The dashed black line represents the addition of the two processes, the SSC measured in the experiment. The straight dashed black line represents the linear regression of the mass erosion steps that determined the critical mass erosion threshold ([Pa]).

SuppTab 3.D: Erosion data summary

Characteristic	0, N = 9311	1, N = 4441	2, N = 4681
Step number	6 (3, 10)	16 (12, 19)	16 (13, 19)
Sec_Palier	393+/-318	859+/-255	910+/-254
Bed shear stress (Pa)
Mean+/-SD	1.86+/-1.87	5.16+/-1.95	5.31+/-1.85
Range	0.06 - 8.81	0.64 - 9.95	1.10 - 10.15
Shear velocity (cm.s-1)
Mean+/-SD	3.77+/-1.97	6.95+/-1.43	7.08+/-1.29
Range	0.74 - 9.28	2.51 - 9.86	3.28 - 9.95
1 Median (IQR); Mean+/-SD

Controls vs temperature

SuppFig 3.E: Controls data ANOVA results versus temperature for A) Qfluff and B) BSS mass threshold

3.2.3 Mass erosion threshold

SuppFig 3.F: Critical bed shear stress (BSSmass [Pa]) vs the different metabolic rate evaluation [mW.m^{-2}]: the measured respiration rate (A), the Itot with the mesocosm temperature (B) and the Itot with the flume temperature (C) and their regression line. Note that the scales are Box-Cox transformed, and the models were made on transformed data.

ANCOVA results 3D

SuppFig 3.G: ANCOVA results

SuppTab 3.E: ANCOVA results

BSS_Pa_Crit_Mass_Ssc..y_tf ~ S1_Itot_meso_mWm2_Ero + S2_Itot_meso_mWm2_Ero + Mumo_txt
Characteristic	Beta1	SE2	p-value
(Intercept)	1.3487***	0.079	8.151 × 10−28
S. plana Itot (mW/m²)	-0.0025	0.004	0.532
H. diversicolor Itot (mW/m²)	0.0132*	0.006	0.038
Duo	NA*		0.018
Control	0.3743**	0.119	0.002
S. plana	0.1284	0.139	0.358
S. plana & (H. diversicolor)	-0.0131	0.084	0.876
(S. plana) & H. diversicolor	-0.1238	0.089	0.167
H. diversicolor	-0.3659*	0.141	0.029
No. Obs. = 84; R² = 0.148; AIC = 85.3
Anova, F(4,77) = 3.18, p = 0.018, eta2[g] = 0.142
BSS_Pa_Crit_Mass_Ssc..y_tf ~ S1_Itot_meso_mWm2_Ero + S2_Itot_meso_mWm2_Ero + Mumo_txt post-hoc tests
Residuals are not normal - Shapiro-Wilk: stat = 0.965, p-value = 0.0208 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 1.864, p-value = 0.125 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.554, p-value = 0.741 (α=0.1)
There are 0 outliers in **
1 *p<0.05; **p<0.01; ***p<0.001
2 SE = Standard Error

Two species 3D plot

SuppFig 3.H: BSS versus metabolic rate of the two species in same sample

Regression coefficients table

SuppTab 3.F: BSS vs metabolic rates of each species of duo regression coefficients

	Mumo_txt	Intercept	S1	S2	gcd.r.squared	p_signif	Nb obs
BSS_Pa_Crit_Mass_Ssc	All	1.46e+00 [1.31e+00, 1.61e+00]	-2.16e-03 [-7.78e-03, 3.47e-03]	-1.80e-03 [-9.95e-03, 6.34e-03]	0.008		84
	Control	1.72e+00 [1.47e+00, 1.98e+00]	NA [NA, NA]	NA [NA, NA]	0.000	-	11
	S. plana	1.42e+00 [9.74e-01, 1.86e+00]	-7.65e-04 [-1.20e-02, 1.04e-02]	NA [NA, NA]	0.001		19
	S. plana & (H. diversicolor)	1.50e+00 [1.08e+00, 1.91e+00]	-2.11e-04 [-3.71e-02, 3.66e-02]	-1.73e-02 [-9.03e-02, 5.57e-02]	0.037		19
	(S. plana) & H. diversicolor	1.33e+00 [9.93e-01, 1.66e+00]	-1.09e-02 [-1.06e-01, 8.40e-02]	1.07e-02 [-4.05e-02, 6.18e-02]	0.024		18
	H. diversicolor	8.45e-01 [4.12e-01, 1.28e+00]	NA [NA, NA]	1.88e-02 [3.01e-03, 3.46e-02]	0.300	*	17

ANCOVA vs Temperature

SuppFig 3.I: ANCOVA results

SuppTab 3.G: ANCOVA results

BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Cond_Fact_txt
Characteristic	Beta1	SE2	p-value
(Intercept)	1.55275***	0.076	<0.001
Itot at mesocosm temperature (mW/m²)	-0.00635*	0.003	0.030
Cond_Fact_txt	NA**		0.005
T. medium	0.03184	0.059	0.6
T. low	-0.20741**	0.063	0.002
T. high	0.17558*	0.067	0.015
No. Obs. = 84; R² = 0.131; AIC = 81.0
Anova, F(2,80) = 5.7, p = 0.005, eta2[g] = 0.125
BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Cond_Fact_txt post-hoc tests
Residuals are not normal - Shapiro-Wilk: stat = 0.969, p-value = 0.0406 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 1.500, p-value = 0.229 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.566, p-value = 0.832 (α=0.1)
There are 0 outliers in **
1 *p<0.05; **p<0.01; ***p<0.001
2 SE = Standard Error

ANCOVA vs Duos

SuppFig 3.J: ANCOVA results

SuppTab 3.H: ANCOVA results

BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Mumo_txt
Characteristic	Beta1	SE2	p-value
(Intercept)	1.38715***	0.078	<0.001
Itot at mesocosm temperature (mW/m²)	0.00247	0.003	0.4
Duo	NA		0.086
Control	0.33586**	0.120	0.006
S. plana	-0.07961	0.092	0.4
S. plana & (H. diversicolor)	-0.05926	0.082	0.5
(S. plana) & H. diversicolor	-0.05556	0.083	0.5
H. diversicolor	-0.14143	0.086	0.3
No. Obs. = 84; R² = 0.105; AIC = 87.5
Anova, F(4,78) = 2.12, p = 0.086, eta2[g] = 0.098
BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Mumo_txt post-hoc tests
Residuals are not normal - Shapiro-Wilk: stat = 0.969, p-value = 0.0393 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 1.475, p-value = 0.218 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.538, p-value = 0.692 (α=0.1)
There are 0 outliers in **
1 *p<0.05; **p<0.01; ***p<0.001
2 SE = Standard Error

ANCOVA vs Duos & Temperature

SuppFig 3.K: ANCOVA results

SuppTab 3.I: ANCOVA results

BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Mumo_txt + Cond_Fact_txt
Characteristic	Beta1	SE2	p-value
(Intercept)	1.49480***	0.089	<0.001
Itot at mesocosm temperature (mW/m²)	-0.00292	0.004	0.4
Duo	NA		0.4
Control	0.22246	0.125	0.079
S. plana	-0.01174	0.094	>0.9
S. plana & (H. diversicolor)	-0.05681	0.079	0.5
(S. plana) & H. diversicolor	-0.04548	0.081	0.6
H. diversicolor	-0.10843	0.085	0.5
Cond_Fact_txt	NA*		0.040
T. medium	0.03165	0.059	0.6
T. low	-0.17269*	0.068	0.013
T. high	0.14104	0.071	0.077
No. Obs. = 84; R² = 0.177; AIC = 84.4
Anova, F(2,76) = 3.35, p = 0.04, eta2[g] = 0.081
BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Mumo_txt + Cond_Fact_txt post-hoc tests
Residuals are not normal - Shapiro-Wilk: stat = 0.965, p-value = 0.0212 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 1.141, p-value = 0.34 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.519, p-value = 0.6 (α=0.1)
There are 0 outliers in **
1 *p<0.05; **p<0.01; ***p<0.001
2 SE = Standard Error

Conditions of application

SuppTab 3.J: Data set description and application conditions

Variable	Control, N = 111	S. plana, N = 191	S. plana & (H. diversicolor), N = 191	(S. plana) & H. diversicolor, N = 181	H. diversicolor, N = 171	Overall, N = 841
BSS_Pa_Crit_Mass_Ssc (dependent)	5.08 (2.24)	3.50 (2.10)	3.29 (1.58)	3.20 (1.19)	3.06 (1.66)	3.50 (1.82)
Itot at mesocosm temperature (mW/m²) (covariate)	0 (0)	34 (21)	22 (11)	22 (12)	25 (13)	22 (17)
Temperature level
T. medium	5	6	6	6	6	29
T. low	3	6	6	6	6	27
T. high	3	7	7	6	5	28
BSS_Pa_Crit_Mass_Ssc normality test
Data are not normal - Shapiro-Wilk: stat=0.945, p-value=0.00129 (α=0.1).
Data transformation - Box-Cox λ = -0.010; λ2 = 1
Transformed data are normal - Shapiro-Wilk: stat = 0.983, p-value = 0.352 (α=0.1)
Treatments subgroup check
Variances are homogeneic - Levene: F value = 1.179, p-value = 0.311 - (α=0.1)
Independence of covariate: Mumo_txt; Cond_Fact_txt have a significant relation with covariate
Regression slopes homogeneity is verified
BSS_Pa_Crit_Mass_Ssc..y_tf ~ Itot_meso_mWm2_Ero + Mumo_txt + Cond_Fact_txt post-hoc tests
Residuals are not normal - Shapiro-Wilk: stat = 0.965, p-value = 0.0212 - (α=0.1)
Residuals variances are homogeneic - Levene: stat = 1.141, p-value = 0.34 - (α=0.1)
Residuals are homoscedastic - Harrison-McCabe: statistic = 0.519, p-value = 0.608 (α=0.1)
There are 0 outliers in **
1 Mean (SD); n

3.3 Results tables

Global

SuppTab 3.K: Linear regressions data (ax+b equation, R² and p-value)

		Respiration_rate_mWm2				Itot_meso_mWm2_Ero				Biomass_gAFDWm2
		All	T. medium	T. low	T. high	All	T. medium	T. low	T. high	All	T. medium	T. low	T. high
BSS_Pa_Crit_Mass_Ssc		-1.479e-03 x +1.455 r²=0.007 (n=84)	-1.416e-02 x +1.769 r²=0.335 * (n=29)**	1.243e-03 x +1.230 r²=0.003 (n=27)	8.246e-04 x +1.483 r²=0.006 (n=28)	-2.071e-03 x +1.460 r²=0.008 (n=84)	-2.303e-02 x +1.904 r²=0.410 * (n=29)**	2.176e-03 x +1.226 r²=0.002 (n=27)	-6.459e-04 x +1.537 r²=0.002 (n=28)	-1.791e-02 x +1.557 r²=0.066 * (n=84)	-4.365e-02 x +1.796 r²=0.332 (n=29)**	4.841e-03 x +1.218 r²=0.005 (n=27)	-9.179e-03 x +1.593 r²=0.032 (n=28)
	S. plana	4.411e-04 x +1.378 r²=0.000 (n=19)	-3.750e-02 x +2.223 r²=0.857 (n=6)**	1.503e-02 x +0.919 r²=0.098 (n=6)	2.145e-03 x +1.402 r²=0.025 (n=7)	-7.651e-04 x +1.417 r²=0.001 (n=19)	-3.017e-02 x +2.350 r²=0.644 · (n=6)	1.339e-02 x +0.987 r²=0.036 (n=6)	-3.265e-03 x +1.665 r²=0.034 (n=7)	-2.406e-02 x +1.702 r²=0.114 (n=19)	-5.362e-02 x +2.168 r²=0.627 · (n=6)	1.519e-02 x +1.034 r²=0.036 (n=6)	-2.432e-02 x +1.815 r²=0.166 (n=7)
	S. plana & (H. diversicolor)	-5.379e-03 x +1.523 r²=0.040 (n=19)	-2.466e-02 x +1.952 r²=0.258 (n=6)	-1.155e-03 x +1.297 r²=0.002 (n=6)	-1.587e-02 x +2.075 r²=0.661 * (n=7)	-5.607e-03 x +1.504 r²=0.030 (n=19)	-3.742e-02 x +2.088 r²=0.722 * (n=6)	1.755e-02 x +1.044 r²=0.074 (n=6)	-2.028e-02 x +2.154 r²=0.647 * (n=7)	-3.982e-02 x +1.718 r²=0.203 · (n=19)	-7.047e-02 x +1.930 r²=0.698 * (n=6)	1.891e-02 x +1.120 r²=0.049 (n=6)	-6.206e-02 x +2.049 r²=0.678 * (n=7)
	(S. plana) & H. diversicolor	2.063e-03 x +1.312 r²=0.026 (n=18)	-2.166e-03 x +1.512 r²=0.008 (n=6)	7.227e-03 x +1.179 r²=0.101 (n=6)	3.029e-03 x +1.198 r²=0.143 (n=6)	3.227e-03 x +1.315 r²=0.018 (n=18)	-8.963e-03 x +1.612 r²=0.040 (n=6)	2.073e-02 x +1.066 r²=0.222 (n=6)	7.630e-03 x +1.100 r²=0.154 (n=6)	1.635e-02 x +1.262 r²=0.048 (n=18)	-1.723e-02 x +1.566 r²=0.033 (n=6)	3.006e-02 x +1.148 r²=0.164 (n=6)	2.327e-02 x +1.155 r²=0.151 (n=6)
	H. diversicolor	3.312e-03 x +1.188 r²=0.050 (n=17)	-4.245e-03 x +1.264 r²=0.127 (n=6)	4.482e-03 x +0.940 r²=0.069 (n=6)	-1.110e-03 x +1.812 r²=0.066 (n=5)	1.879e-02 x +0.845 r²=0.300 * (n=17)	1.922e-02 x +0.735 r²=0.231 (n=6)	7.359e-03 x +0.949 r²=0.027 (n=6)	9.326e-04 x +1.719 r²=0.012 (n=5)	2.000e-02 x +1.154 r²=0.037 (n=17)	5.236e-02 x +0.797 r²=0.286 (n=6)	1.139e-02 x +0.988 r²=0.021 (n=6)	-1.929e-04 x +1.754 r²=0.000 (n=5)
BSS_Pa_Crit_Mass_Visu		1.745e-03 x +1.262 r²=0.010 (n=82)	1.184e-03 x +1.240 r²=0.003 (n=28)	-1.004e-03 x +1.268 r²=0.002 (n=27)	9.002e-04 x +1.384 r²=0.004 (n=27)	2.567e-03 x +1.252 r²=0.011 (n=82)	-5.259e-04 x +1.277 r²=0.000 (n=28)	-7.232e-03 x +1.348 r²=0.027 (n=27)	1.948e-03 x +1.352 r²=0.009 (n=27)	-3.278e-03 x +1.338 r²=0.002 (n=82)	-1.478e-03 x +1.279 r²=0.000 (n=28)	-9.608e-03 x +1.323 r²=0.021 (n=27)	-2.152e-03 x +1.439 r²=0.001 (n=27)
	S. plana	7.409e-03 x +1.097 r²=0.228 * (n=19)	1.294e-02 x +0.911 r²=0.437 (n=6)	-3.169e-04 x +1.225 r²=0.000 (n=6)	4.252e-03 x +1.318 r²=0.112 (n=7)	5.547e-03 x +1.124 r²=0.121 (n=19)	1.235e-02 x +0.809 r²=0.463 (n=6)	-1.069e-02 x +1.403 r²=0.054 (n=6)	-9.221e-04 x +1.553 r²=0.003 (n=7)	1.544e-03 x +1.292 r²=0.001 (n=19)	2.114e-02 x +0.894 r²=0.418 (n=6)	-1.267e-02 x +1.371 r²=0.059 (n=6)	-1.357e-02 x +1.683 r²=0.058 (n=7)
	S. plana & (H. diversicolor)	-1.624e-02 x +1.703 r²=0.195 · (n=18)	3.943e-03 x +1.091 r²=0.015 (n=6)	-1.395e-02 x +1.506 r²=0.135 (n=6)	-3.373e-02 x +2.471 r²=0.617 · (n=6)	-1.548e-02 x +1.626 r²=0.127 (n=18)	-2.689e-02 x +1.779 r²=0.832 * (n=6)	-9.005e-03 x +1.376 r²=0.011 (n=6)	-4.110e-02 x +2.667 r²=0.526 (n=6)	-6.234e-02 x +1.825 r²=0.273 * (n=18)	-5.194e-02 x +1.678 r²=0.845 (n=6)**	-1.758e-02 x +1.402 r²=0.024 (n=6)	-1.261e-01 x +2.457 r²=0.557 · (n=6)
	(S. plana) & H. diversicolor	-1.551e-05 x +1.379 r²=0.000 (n=17)	8.505e-03 x +1.131 r²=0.135 (n=6)	1.527e-03 x +1.357 r²=0.005 (n=6)	-7.415e-04 x +1.365 r²=0.006 (n=5)	5.552e-04 x +1.367 r²=0.000 (n=17)	-1.135e-03 x +1.424 r²=0.001 (n=6)	6.742e-03 x +1.299 r²=0.024 (n=6)	4.565e-03 x +1.178 r²=0.038 (n=5)	5.437e-03 x +1.337 r²=0.005 (n=17)	1.662e-03 x +1.391 r²=0.000 (n=6)	8.239e-03 x +1.336 r²=0.013 (n=6)	7.970e-03 x +1.261 r²=0.012 (n=5)
	H. diversicolor	3.383e-03 x +1.165 r²=0.074 (n=18)	-2.132e-03 x +1.311 r²=0.101 (n=6)	1.074e-02 x +0.659 r²=0.597 · (n=6)	-5.749e-03 x +1.929 r²=0.403 (n=6)	1.108e-02 x +0.993 r²=0.227 * (n=18)	1.385e-02 x +0.952 r²=0.379 (n=6)	1.150e-02 x +0.791 r²=0.099 (n=6)	-6.087e-03 x +1.859 r²=0.206 (n=6)	1.311e-02 x +1.185 r²=0.025 (n=18)	3.610e-02 x +1.008 r²=0.430 (n=6)	2.048e-02 x +0.830 r²=0.102 (n=6)	-2.559e-02 x +1.841 r²=0.263 (n=6)

Constrast tables

SuppTab 3.L: Significative differences between regression slopes

		Respiration_rate_mWm2	Itot_meso_mWm2_Ero	Biomass_gAFDWm2
BSS_Pa_Crit_Mass_Ssc	pairwise ~ Cond_Fact_txt	T. medium - T. high * T. low - T. high ·	T. medium - T. high T. low - T. high	-
	pairwise ~ Cond_Fact_txt | Mumo_txt	H. diversicolor T. medium - T. high · H. diversicolor T. low - T. high ·	H. diversicolor T. medium - T. high · H. diversicolor T. low - T. high *	H. diversicolor T. low - T. high ·

4 Supplementary data

4.1 Session information

Expand for R Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.0 (2024-04-24 ucrt)
 os       Windows 11 x64 (build 22631)
 system   x86_64, mingw32
 ui       RTerm
 language en
 collate  French_France.utf8
 ctype    French_France.utf8
 tz       Europe/Paris
 date     2024-05-23
 pandoc   3.1.11 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
 quarto   1.4.554 @ C:\\PROGRA~1\\Quarto\\bin\\quarto.exe

─ Packages ───────────────────────────────────────────────────────────────────
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